• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

多药理学:药物研发中的挑战与机遇

Polypharmacology: challenges and opportunities in drug discovery.

作者信息

Anighoro Andrew, Bajorath Jürgen, Rastelli Giulio

机构信息

Life Sciences Department, University of Modena and Reggio Emilia , Via Campi 183, 41125 Modena, Italy.

出版信息

J Med Chem. 2014 Oct 9;57(19):7874-87. doi: 10.1021/jm5006463. Epub 2014 Jun 25.

DOI:10.1021/jm5006463
PMID:24946140
Abstract

At present, the legendary magic bullet, i.e., a drug with high potency and selectivity toward a specific biological target, shares the spotlight with an emerging and alternative polypharmacology approach. Polypharmacology suggests that more effective drugs can be developed by specifically modulating multiple targets. It is generally thought that complex diseases such as cancer and central nervous system diseases may require complex therapeutic approaches. In this respect, a drug that "hits" multiple sensitive nodes belonging to a network of interacting targets offers the potential for higher efficacy and may limit drawbacks generally arising from the use of a single-target drug or a combination of multiple drugs. In this review, we will compare advantages and disadvantages of multitarget versus combination therapies, discuss potential drug promiscuity arising from off-target effects, comment on drug repurposing, and introduce approaches to the computational design of multitarget drugs.

摘要

目前,传说中的神奇子弹,即对特定生物靶点具有高效力和选择性的药物,正与一种新兴的、替代性的多药理学方法共同成为焦点。多药理学表明,通过特异性调节多个靶点可以开发出更有效的药物。人们普遍认为,癌症和中枢神经系统疾病等复杂疾病可能需要复杂的治疗方法。在这方面,一种“击中”属于相互作用靶点网络的多个敏感节点的药物具有更高疗效的潜力,并且可能限制通常因使用单靶点药物或多种药物组合而产生的缺点。在本综述中,我们将比较多靶点疗法与联合疗法的优缺点,讨论由脱靶效应引起的潜在药物混杂性,评论药物再利用,并介绍多靶点药物的计算设计方法。

相似文献

1
Polypharmacology: challenges and opportunities in drug discovery.多药理学:药物研发中的挑战与机遇
J Med Chem. 2014 Oct 9;57(19):7874-87. doi: 10.1021/jm5006463. Epub 2014 Jun 25.
2
Polypharmacology in Drug Discovery: A Review from Systems Pharmacology Perspective.药物发现中的多药理学:从系统药理学角度的综述
Curr Pharm Des. 2016;22(21):3171-81. doi: 10.2174/1381612822666160224142812.
3
Polypharmacology - foe or friend?多靶标药物疗法——敌是友?
J Med Chem. 2013 Nov 27;56(22):8955-71. doi: 10.1021/jm400856t. Epub 2013 Aug 22.
4
GES polypharmacology fingerprints: a novel approach for drug repositioning.基因表达系列分析(GES)多药理学指纹图谱:一种药物重新定位的新方法。
J Chem Inf Model. 2014 Mar 24;54(3):720-34. doi: 10.1021/ci4006723. Epub 2014 Feb 17.
5
Epigenetic polypharmacology: from combination therapy to multitargeted drugs.表观遗传学多药理学:从联合疗法到多靶点药物
Clin Epigenetics. 2016 Oct 12;8:105. doi: 10.1186/s13148-016-0271-9. eCollection 2016.
6
Turning liabilities into opportunities: Off-target based drug repurposing in cancer.变劣势为优势:基于非靶标药物的癌症再利用。
Semin Cancer Biol. 2021 Jan;68:209-229. doi: 10.1016/j.semcancer.2020.02.003. Epub 2020 Feb 7.
7
Computational Multitarget Drug Design.计算多靶标药物设计。
J Chem Inf Model. 2017 Mar 27;57(3):403-412. doi: 10.1021/acs.jcim.6b00491. Epub 2017 Feb 23.
8
Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery.提高多靶点药物发现中多药联用的疗效-安全性平衡。
Expert Opin Drug Discov. 2018 Feb;13(2):179-192. doi: 10.1080/17460441.2018.1413089. Epub 2017 Dec 12.
9
Toward structure-multiple activity relationships (SMARts) using computational approaches: A polypharmacological perspective.采用计算方法研究结构-多种活性关系(SMARts):多药理学视角。
Drug Discov Today. 2024 Jul;29(7):104046. doi: 10.1016/j.drudis.2024.104046. Epub 2024 May 27.
10
Drugs Polypharmacology by In Silico Methods: New Opportunities in Drug Discovery.基于计算机模拟方法的药物多药理学:药物发现的新机遇
Curr Pharm Des. 2016;22(21):3073-81. doi: 10.2174/1381612822666160224142323.

引用本文的文献

1
Chlorogenic Acid and Cinnamaldehyde in Breast Cancer Cells: Predictive Examination of Pharmacokinetics and Binding Thermodynamics with the Key Mediators of PI3K/Akt Signaling.乳腺癌细胞中的绿原酸和肉桂醛:与PI3K/Akt信号关键介质的药代动力学及结合热力学预测性研究
Biomedicines. 2025 Jul 24;13(8):1810. doi: 10.3390/biomedicines13081810.
2
Ascending single-dose study of the safety, pharmacokinetics, and pharmacodynamics of CSTI-500, a novel monoamine triple reuptake inhibitor, first-in-human.新型单胺三重再摄取抑制剂CSTI-500首次人体单剂量递增安全性、药代动力学和药效学研究。
Psychopharmacology (Berl). 2025 Aug 11. doi: 10.1007/s00213-025-06861-4.
3
Design, synthesis and biological evaluation of novel bis(indolyl)-tetrazine derivatives as anti-breast cancer agents.
新型双(吲哚基)-四嗪衍生物作为抗乳腺癌药物的设计、合成及生物学评价
RSC Med Chem. 2025 Jul 23. doi: 10.1039/d5md00297d.
4
Polypharmacology-Driven Discovery of ZAK-I-57: A Potent Multi-Targeted Benzoxazinone Small Molecule for Hepatocellular Carcinoma Therapy.基于多药理学的ZAK-I-57发现:一种用于肝细胞癌治疗的强效多靶点苯并恶嗪酮小分子
MedComm (2020). 2025 Jul 27;6(8):e70291. doi: 10.1002/mco2.70291. eCollection 2025 Aug.
5
AI-Driven Polypharmacology in Small-Molecule Drug Discovery.小分子药物发现中的人工智能驱动多药理学
Int J Mol Sci. 2025 Jul 21;26(14):6996. doi: 10.3390/ijms26146996.
6
Effects of Betulinic Acid and Ursolic Acid on IL-17-Induced CCL20 Release in Normal Human Epidermal Keratinocytes.桦木酸和熊果酸对白细胞介素-17诱导正常人表皮角质形成细胞释放CCL20的影响。
Life (Basel). 2025 Jul 4;15(7):1073. doi: 10.3390/life15071073.
7
The Destructive Cycle in Bronchopulmonary Dysplasia: The Rationale for Systems Pharmacology Therapeutics.支气管肺发育不良中的破坏循环:系统药理学治疗原理
Antioxidants (Basel). 2025 Jul 10;14(7):844. doi: 10.3390/antiox14070844.
8
Structure-Based Discovery of Hsp90/HDAC6 Dual Inhibitors Targeting Aggressive Prostate Cancer.基于结构的Hsp90/HDAC6双重抑制剂发现,靶向侵袭性前列腺癌
J Med Chem. 2025 Aug 14;68(15):15738-15765. doi: 10.1021/acs.jmedchem.5c00717. Epub 2025 Jul 23.
9
Recent advances in focal adhesion kinase (FAK)-targeting antitumor agents.聚焦粘附激酶(FAK)靶向抗肿瘤药物的最新进展。
RSC Adv. 2025 Jun 20;15(26):20957-20984. doi: 10.1039/d5ra01880c. eCollection 2025 Jun 16.
10
A 3D generation framework using diffusion model and reinforcement learning to generate multi-target compounds with desired properties.一种使用扩散模型和强化学习来生成具有所需特性的多靶点化合物的3D生成框架。
J Cheminform. 2025 Jun 4;17(1):93. doi: 10.1186/s13321-025-01035-y.